Modeling to Predict Cases of Hantavirus Pulmonary Syndrome in Chile

Abstract

BackgroundHantavirus pulmonary syndrome (HPS) is a life threatening disease transmitted by the rodent Oligoryzomys longicaudatus in Chile. Hantavirus outbreaks are typically small and geographically confined. Several studies have estimated risk based on spatial and temporal distribution of cases in relation to climate and environmental variables, but few have considered climatological modeling of HPS incidence for monitoring and forecasting purposes.MethodologyMonthly counts of confirmed HPS cases were obtained from the Chilean Ministry of Health for 2001–2012. There were an estimated 667 confirmed HPS cases. The data suggested a seasonal trend, which appeared to correlate with changes in climatological variables such as temperature, precipitation, and humidity. We considered several Auto Regressive Integrated Moving Average (ARIMA) time-series models and regression models with ARIMA errors with one or a combination of these climate variables as covariates. We adopted an information-theoretic approach to model ranking and selection. Data from 2001–2009 were used in fitting and data from January 2010 to December 2012 were used for one-step-ahead predictions.ResultsWe focused on six models. In a baseline model, future HPS cases were forecasted from previous incidence; the other models included climate variables as covariates. The baseline model had a Corrected Akaike Information Criterion (AICc) of 444.98, and the top ranked model, which included precipitation, had an AICc of 437.62. Although the AICc of the top ranked model only provided a 1.65% improvement to the baseline AICc, the empirical support was 39 times stronger relative to the baseline model.ConclusionsInstead of choosing a single model, we present a set of candidate models that can be used in modeling and forecasting confirmed HPS cases in Chile. The models can be improved by using data at the regional level and easily extended to other countries with seasonal incidence of HPS.

Distributional ecology of Andes hantavirus: a macroecological approach

“…Our exploration was temporally static, yet hantavirus transmission may have a significant seasonal dimension. For example, most human HPS cases in Chile and Argentina are reported during spring and summer, when rodent abundances and seroprevalences tend to be high [ 62 , 64 , 75 , 78 , 79 ]. Additionally, many human activities concentrating human presence in situations of risk, such as farming and tourism, may occur chiefly in summer [ 26 , 39 , 64 ].…”

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“…The general structure of the model is as follows: Where n t is assumed to follow an ARIMA model. When y t and x t are differenced once, the combined regression with ARIMA (1,1,1) errors model is: Where y ′ t = y t − y t −1 , x ′ t,i = x t,i − x t −1 , n ′ t = n t − n t −1 and e t is a white noise series [ 17 ].…”

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“…This could be explained by the fact that chigger mites are more likely to grow and attach to rodents in humid environments, further affecting the onset of TD. A study in Chile revealed that chigger mites survive and reproduce well at a relative humidity of above 50% but their activity reduce when the relative humidity is below 50% [ 34 ]. Around the end of 2014, there was a dissociation in the general consistent trend between rainfall and reported cases, with the number of cases remaining high even with a drop in the rainfall level, which may be because the reported cases peaked in 2014 but the rainfall level fluctuated with the season every year.…”